**5. Conclusions**

In this paper, the frequency regulation method—based on fuzzy neural network control—is proposed to regulate the temperature set-point of TCLs in the ancillary service market. Due to the strong dependence of tracking accuracy on membership functions and connection weight coefficients, the combination of offline hybrid algorithms and online BP algorithms can better optimize the control parameters. Finally, the conclusion obtained from the simulation results is that the fuzzy neural network control has prominent advantages of tracking accuracy without modeling the aggregated TCLs.

**Author Contributions:** K.M. contributed the idea; Z.Q. wrote the paper; C.X. conceived and designed the experiments; Z.J. provided the software.

**Funding:** This work was supported by the National Key Research and Development Program of China under Grant 2016YFF0200105 and National Natural Science Foundation of China under Grant 61573303.

**Conflicts of Interest:** The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.
